Texture Analysis of Brodatz Images Using Statistical Methods


Textures are one of the important features in computer vision for manyapplications. Most of attention has been focused on the texture features. Animportant approach to region description is to quantify its texture content.Although no formal definition of texture exists, intuitively this descriptor providesmeasures of properties such as smoothing and regularity. The principal approachesused in image processing to describe the texture of an image region are statistical,structural, and spectral. In this paper the features were constructed using differentstatistical methods. These are auto-correlation, edge frequency, primitive-lengthand law’s method; all these methods were used for texture analysis of Brodatzimages. The result showed that the law’s autocorrelation method yields the bestresult.